Data mining-based optimal selection method for reservoir multi-target dispatching rule parameters

A technology of data mining and multi-objective optimization, applied in other database retrieval, data processing applications, electrical digital data processing and other directions, can solve the problem of not avoiding redundant information, and achieve improved calculation efficiency, reduced optimization costs, and simple scheduling. the effect of the rule

Active Publication Date: 2016-10-12
WUHAN UNIV
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Problems solved by technology

Existing reservoir multi-objective optimization models often directly optimize the reservoir dispatching rules without avoiding the redundant informa

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  • Data mining-based optimal selection method for reservoir multi-target dispatching rule parameters
  • Data mining-based optimal selection method for reservoir multi-target dispatching rule parameters
  • Data mining-based optimal selection method for reservoir multi-target dispatching rule parameters

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[0038] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0039] The present invention combines the multi-objective optimal scheduling model of the reservoir with the random forest model, and proposes a method for optimizing the parameters of the multi-objective scheduling rules of the reservoir based on data mining. The flow chart for optimizing the parameters of the multi-objective scheduling rules of the reservoir is as follows figure 1 shown.

[0040] Concrete realization of the present invention comprises the following steps:

[0041] Step 1. Collect data such as the inflow flow observed at the upstream statio...

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Abstract

The invention discloses a data mining-based optimal selection method for reservoir multi-target dispatching rule parameters. The method comprises the steps of obtaining a reservoir multi-target dispatching non-inferior solution set by adopting a multi-target optimization algorithm; establishing a relationship between all reservoir dispatching rule parameters and the non-inferior solution set by utilizing a random forest model; and optimally selecting a reservoir multi-target dispatching rule parameter with a maximum information quantity by evaluating a prediction effect of each parameter on the non-inferior solution set. According to the method, reservoir optimization dispatching information can be effectively utilized, so that the number of parameters in a reservoir dispatching rule is greatly reduced, the efficiency of solving a reservoir multi-target optimization dispatching model is improved, and a simpler and high-operability reference basis is provided for scientific decision-making of a reservoir.

Description

technical field [0001] The invention belongs to the technical field of reservoir dispatching, and relates to a method for optimizing parameters of multi-objective dispatching rules of reservoirs based on data mining. Background technique [0002] As a tool for runoff regulation, reservoirs play an important role in making water resources more suitable for the development of human society and maintaining the ecological environment. Reservoir regulation rules are a way to guide the operation of reservoirs. With social progress and economic development, people have more demands on the utilization of water resources. Generally, intelligent multi-objective optimization algorithms are used to obtain reservoir dispatching rules that meet various water demands. However, multi-objective optimization problems of reservoirs often have nonlinear and high-dimensional characteristics, which increase the optimization cost of intelligent algorithms. How to optimize the most valuable paramet...

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Application Information

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IPC IPC(8): G06Q50/06G06F17/30G06F19/00
CPCG06F16/90G06Q50/06G16Z99/00
Inventor 郭生练杨光李立平尹家波刘章君
Owner WUHAN UNIV
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